NDLI: Automatic Identification of Shaft Orbits for Steam Turbine Generator Sets

Content Provider	IEEE Xplore Digital Library
Author	Changfeng Yan Hao Zhang Hui Li Li Yang Wen Huang
Copyright Year	2009
Abstract	The shaft orbits and dynamic characteristics of the shaft centre orbit contain abundant information for the fault diagnosis of rotating machinery and reflect different faults of rotating machine. Therefore the shaft orbits recognition plays an important role in the fault diagnosis of steam turbine generator set. An automatic identification method of shaft orbit for steam turbine generator sets is proposed in this paper. The median morphological filter combining the open-closing with clos-opening is used to eliminate the noise in the original X and Y vibration signals. Then the seven invariant moment feature are extracted from the shaft orbit reconstructed. Input the seven invariant moments to the trained BP neural network, the shaft orbit can be identified automatically. A case is verified this model. It is shown that this model is feasible and high precision for identify the shaft orbit in fault diagnosis.
Starting Page	53
Ending Page	57
File Size	351525
Page Count	5
File Format	PDF
ISBN	9780769535715
DOI	10.1109/GCIS.2009.239
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	steam turbine generator sets Extraterrestrial measurements Orbits Shafts Fault diagnosis Filters BP neural network shaft orbit Neural networks morphological filter Feature extraction Pollution measurement Turbines Power generation invariant moment
Content Type	Text
Resource Type	Article

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